Behavioral economic methods predict future COVID-19 vaccination.

Area of Science:

• Behavioral Economics
• Public Health
• Vaccinology

Background:

• Increasing vaccine utilization is crucial for managing infectious diseases like COVID-19.
• Behavioral economic methods offer scalable approaches to understand health behavior engagement.
• Existing research often uses cross-sectional designs and well-established behaviors, limiting understanding of novel behaviors.

Purpose of the Study:

• To evaluate the predictive validity of a behavioral economic hypothetical purchase task for a novel behavior (COVID-19 vaccination).
• To determine if hypothetical task responses predict real-world vaccination status.
• To assess the utility of behavioral economic methods for forecasting uptake of new vaccines.

Main Methods:

• A cohort of 333 participants completed a hypothetical purchase task assessing willingness to receive a COVID-19 vaccine in August 2020.
• Vaccination status was measured via follow-up assessments in June and November 2021, after vaccines became widely available.
• Predictive models controlled for factors including political orientation, delay discounting, and prior flu vaccination history.

Main Results:

• Hypothetical vaccine demand significantly predicted actual COVID-19 vaccination status.
• This predictive validity was observed even for a behavior with no prior real-world experience for participants.
• The findings demonstrate the utility of behavioral economic tasks for forecasting novel health behaviors.

Conclusions:

• Behavioral economic hypothetical tasks possess predictive validity for novel behaviors like COVID-19 vaccination.
• These methods can effectively forecast vaccination utilization, advancing behavioral economic applications in public health.
• The study supports the use of hypothetical scenarios to predict engagement with new health interventions.